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GrapeL: Combining Graph Pattern Matching and Complex Event Processing

Ehmes, Sebastian ; Fritsche, Lars ; Altenhofen, Konrad
Babur, Önder ; Denil, Joachim ; Vogel-Heuser, Birgit (eds.) (2020):
GrapeL: Combining Graph Pattern Matching and Complex Event Processing.
pp. 180-196, Springer, 1st International Conference on Systems Modelling and Management (ICSMM 2020), virtual Conference, 25.-26.06., ISBN 978-3-030-58166-4,
DOI: 10.1007/978-3-030-58167-1_13,
[Conference or Workshop Item]

Abstract

Incremental Graph Pattern Matching (IGPM) offers an elegant approach to find patterns in graph-based models, reporting newly added and recently removed pattern matches. However, analyzing these matches w.r.t. temporal and causal dependencies can in general only be done by extending not just the IGPM engine but also the underlying model, which often is impractical and sometimes even impossible. Therefore, we transform the stream of pattern matches to a stream of events and employ Complex Event Processing (CEP) to detect such dependencies and derive more complex events from them. For this purpose, we introduce GrapeL as a textual language to specify and generate integrated solutions using both IGPM and CEP to benefit from the synergy of both approaches, which we present in the context of a flight and booking scenario. Finally, we show that our solution can compete with an optimized hand-crafted version without GrapeL and CEP while offering a specification that yields a less tedious and error-prone design process.

Item Type: Conference or Workshop Item
Erschienen: 2020
Editors: Babur, Önder ; Denil, Joachim ; Vogel-Heuser, Birgit
Creators: Ehmes, Sebastian ; Fritsche, Lars ; Altenhofen, Konrad
Title: GrapeL: Combining Graph Pattern Matching and Complex Event Processing
Language: English
Abstract:

Incremental Graph Pattern Matching (IGPM) offers an elegant approach to find patterns in graph-based models, reporting newly added and recently removed pattern matches. However, analyzing these matches w.r.t. temporal and causal dependencies can in general only be done by extending not just the IGPM engine but also the underlying model, which often is impractical and sometimes even impossible. Therefore, we transform the stream of pattern matches to a stream of events and employ Complex Event Processing (CEP) to detect such dependencies and derive more complex events from them. For this purpose, we introduce GrapeL as a textual language to specify and generate integrated solutions using both IGPM and CEP to benefit from the synergy of both approaches, which we present in the context of a flight and booking scenario. Finally, we show that our solution can compete with an optimized hand-crafted version without GrapeL and CEP while offering a specification that yields a less tedious and error-prone design process.

Publisher: Springer
ISBN: 978-3-030-58166-4
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Real-Time Systems
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
Event Title: 1st International Conference on Systems Modelling and Management (ICSMM 2020)
Event Location: virtual Conference
Event Dates: 25.-26.06.
Date Deposited: 20 Nov 2020 08:36
DOI: 10.1007/978-3-030-58167-1_13
Additional Information:

Part of the Communications in Computer and Information Science book series (CCIS, volume 1262)

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